Propriedades estatísticas de bilhares abertos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Relationships between gender, age, family conditions, physical and mental health, and social isolation of elderly caregivers

Background: In an aging population an increasing number of elderly caregivers will be called upon to provide care over a long period, during which time they will be burdened both by caregiving and by the physiological effects of their own aging. Among them there will be more aged male caregivers, who will probably be less prepared than women to become caregivers. The aim of this study was to investigate the relationship between caregivers' gender, age, family income, living arrangements and social support as independent variables, and depressive symptoms, comorbidities, level of frailty, grip strength, walking speed and social isolation, as dependent variables. Methods: 176 elderly people (123 women) were selected from a sample of a population-based study on frailty (n = 900), who had cared for a spouse (79.3%) and/or parents (31.4%) in the past five years (mean age = 71.8 +/- 4.86 years; mean monthly family income in minimum wages = 4.64 +/- 5.14). The study used questionnaires and self-report scales, grip strength and walking speed tests. Results: 65% of participants evaluated caregiving as being very stressful. Univariate analyses of regression showed low family income as a risk factor for depression; being female and low perceived social support as a risk for comorbidities; being 80 years of age and above for low grip strength; and being male for social isolation indicated by discontinuity of activities and social roles. In multivariate analyses of regression, poverty arose as a risk factor for depression and being female for comorbidities. Conclusions: Gender roles, age, income and social support interacted with physical and emotional health, and with the continuity of social participation of elderly caregivers. Special attention must be given to male caregivers.

NMR, Metabonomics and Molecular Profiles: Applications to the Quality Assessment of Foodstuffs

Nuclear Magnetic Resonance (NMR) is a branch of spectroscopy that is based on the fact that many atomic nuclei may be oriented by a strong magnetic field and will absorb radiofrequency radiation at characteristic frequencies. The parameters that can be measured on the resulting spectral lines (line positions, intensities, line widths, multiplicities and transients in time-dependent experi-ments) can be interpreted in terms of molecular structure, conformation, molecular motion and other rate processes. In this way, high resolution (HR) NMR allows performing qualitative and quantitative analysis of samples in solution, in order to determine the structure of molecules in solution and not only. In the past, high-field NMR spectroscopy has mainly concerned with the elucidation of chemical structure in solution, but today is emerging as a powerful exploratory tool for probing biochemical and physical processes. It represents a versatile tool for the analysis of foods. In literature many NMR studies have been reported on different type of food such as wine, olive oil, coffee, fruit juices, milk, meat, egg, starch granules, flour, etc using different NMR techniques. Traditionally, univariate analytical methods have been used to ex-plore spectroscopic data. This method is useful to measure or to se-lect a single descriptive variable from the whole spectrum and , at the end, only this variable is analyzed. This univariate methods ap-proach, applied to HR-NMR data, lead to different problems due especially to the complexity of an NMR spectrum. In fact, the lat-ter is composed of different signals belonging to different mole-cules, but it is also true that the same molecules can be represented by different signals, generally strongly correlated. The univariate methods, in this case, takes in account only one or a few variables, causing a loss of information. Thus, when dealing with complex samples like foodstuff, univariate analysis of spectra data results not enough powerful. Spectra need to be considered in their wholeness and, for analysing them, it must be taken in consideration the whole data matrix: chemometric methods are designed to treat such multivariate data. Multivariate data analysis is used for a number of distinct, differ-ent purposes and the aims can be divided into three main groups: • data description (explorative data structure modelling of any ge-neric n-dimensional data matrix, PCA for example); • regression and prediction (PLS); • classification and prediction of class belongings for new samples (LDA and PLS-DA and ECVA). The aim of this PhD thesis was to verify the possibility of identify-ing and classifying plants or foodstuffs, in different classes, based on the concerted variation in metabolite levels, detected by NMR spectra and using the multivariate data analysis as a tool to inter-pret NMR information. It is important to underline that the results obtained are useful to point out the metabolic consequences of a specific modification on foodstuffs, avoiding the use of a targeted analysis for the different metabolites. The data analysis is performed by applying chemomet-ric multivariate techniques to the NMR dataset of spectra acquired. The research work presented in this thesis is the result of a three years PhD study. This thesis reports the main results obtained from these two main activities: A1) Evaluation of a data pre-processing system in order to mini-mize unwanted sources of variations, due to different instrumental set up, manual spectra processing and to sample preparations arte-facts; A2) Application of multivariate chemiometric models in data analy-sis.

Efficient subsequence alignment of time series

Zeitreihen sind allgegenwärtig. Die Erfassung und Verarbeitung kontinuierlich gemessener Daten ist in allen Bereichen der Naturwissenschaften, Medizin und Finanzwelt vertreten. Das enorme Anwachsen aufgezeichneter Datenmengen, sei es durch automatisierte Monitoring-Systeme oder integrierte Sensoren, bedarf außerordentlich schneller Algorithmen in Theorie und Praxis. Infolgedessen beschäftigt sich diese Arbeit mit der effizienten Berechnung von Teilsequenzalignments. Komplexe Algorithmen wie z.B. Anomaliedetektion, Motivfabfrage oder die unüberwachte Extraktion von prototypischen Bausteinen in Zeitreihen machen exzessiven Gebrauch von diesen Alignments. Darin begründet sich der Bedarf nach schnellen Implementierungen. Diese Arbeit untergliedert sich in drei Ansätze, die sich dieser Herausforderung widmen. Das umfasst vier Alignierungsalgorithmen und ihre Parallelisierung auf CUDA-fähiger Hardware, einen Algorithmus zur Segmentierung von Datenströmen und eine einheitliche Behandlung von Liegruppen-wertigen Zeitreihen.rnrnDer erste Beitrag ist eine vollständige CUDA-Portierung der UCR-Suite, die weltführende Implementierung von Teilsequenzalignierung. Das umfasst ein neues Berechnungsschema zur Ermittlung lokaler Alignierungsgüten unter Verwendung z-normierten euklidischen Abstands, welches auf jeder parallelen Hardware mit Unterstützung für schnelle Fouriertransformation einsetzbar ist. Des Weiteren geben wir eine SIMT-verträgliche Umsetzung der Lower-Bound-Kaskade der UCR-Suite zur effizienten Berechnung lokaler Alignierungsgüten unter Dynamic Time Warping an. Beide CUDA-Implementierungen ermöglichen eine um ein bis zwei Größenordnungen schnellere Berechnung als etablierte Methoden.rnrnAls zweites untersuchen wir zwei Linearzeit-Approximierungen für das elastische Alignment von Teilsequenzen. Auf der einen Seite behandeln wir ein SIMT-verträgliches Relaxierungschema für Greedy DTW und seine effiziente CUDA-Parallelisierung. Auf der anderen Seite führen wir ein neues lokales Abstandsmaß ein, den Gliding Elastic Match (GEM), welches mit der gleichen asymptotischen Zeitkomplexität wie Greedy DTW berechnet werden kann, jedoch eine vollständige Relaxierung der Penalty-Matrix bietet. Weitere Verbesserungen umfassen Invarianz gegen Trends auf der Messachse und uniforme Skalierung auf der Zeitachse. Des Weiteren wird eine Erweiterung von GEM zur Multi-Shape-Segmentierung diskutiert und auf Bewegungsdaten evaluiert. Beide CUDA-Parallelisierung verzeichnen Laufzeitverbesserungen um bis zu zwei Größenordnungen.rnrnDie Behandlung von Zeitreihen beschränkt sich in der Literatur in der Regel auf reellwertige Messdaten. Der dritte Beitrag umfasst eine einheitliche Methode zur Behandlung von Liegruppen-wertigen Zeitreihen. Darauf aufbauend werden Distanzmaße auf der Rotationsgruppe SO(3) und auf der euklidischen Gruppe SE(3) behandelt. Des Weiteren werden speichereffiziente Darstellungen und gruppenkompatible Erweiterungen elastischer Maße diskutiert.

Tumor necrosis factor sensitizes primary murine hepatocytes to Fas/CD95-induced apoptosis in a Bim- and Bid-dependent manner

Fas/CD95 is a critical mediator of cell death in many chronic and acute liver diseases and induces apoptosis in primary hepatocytes in vitro. In contrast, the proinflammatory cytokine tumor necrosis factor α (TNFα) fails to provoke cell death in isolated hepatocytes but has been implicated in hepatocyte apoptosis during liver diseases associated with chronic inflammation. Here we report that TNFα sensitizes primary murine hepatocytes cultured on collagen to Fas ligand (FasL)-induced apoptosis. This synergism is time-dependent and is specifically mediated by TNFα. Fas itself is essential for the sensitization, but neither Fas up-regulation nor endogenous FasL is responsible for this effect. Although FasL is shown to induce Bid-independent apoptosis in hepatocytes cultured on collagen, the sensitizing effect of TNFα is clearly dependent on Bid. Moreover, both c-Jun N-terminal kinase activation and Bim, another B cell lymphoma 2 homology domain 3 (BH3)-only protein, are crucial mediators of TNFα-induced apoptosis sensitization. Bim and Bid activate the mitochondrial amplification loop and induce cytochrome c release, a hallmark of type II apoptosis. The mechanism of TNFα-induced sensitization is supported by a mathematical model that correctly reproduces the biological findings. Finally, our results are physiologically relevant because TNFα also induces sensitivity to agonistic anti-Fas-induced liver damage. CONCLUSION: Our data suggest that TNFα can cooperate with FasL to induce hepatocyte apoptosis by activating the BH3-only proteins Bim and Bid.

Vertical bias in neglect: A question of time?

Neglect is defined as the failure to attend and to orient to the contralesional side of space. A horizontal bias towards the right visual field is a classical finding in patients who suffered from a right-hemispheric stroke. The vertical dimension of spatial attention orienting has only sparsely been investigated so far. The aim of this study was to investigate the specificity of this vertical bias by means of a search task, which taps a more pronounced top-down attentional component. Eye movements and behavioural search performance were measured in thirteen patients with left-sided neglect after right hemispheric stroke and in thirteen age-matched controls. Concerning behavioural performance, patients found significantly less targets than healthy controls in both the upper and lower left quadrant. However, when targets were located in the lower left quadrant, patients needed more visual fixations (and therefore longer search time) to find them, suggesting a time-dependent vertical bias.

Retraining of interjoint arm coordination after stroke using robot-assisted time-independent functional training

We have developed a haptic-based approach for retraining of interjoint coordination following stroke called time-independent functional training (TIFT) and implemented this mode in the ARMin III robotic exoskeleton. The ARMin III robot was developed by Drs. Robert Riener and Tobias Nef at the Swiss Federal Institute of Technology Zurich (Eidgenossische Technische Hochschule Zurich, or ETH Zurich), in Zurich, Switzerland. In the TIFT mode, the robot maintains arm movements within the proper kinematic trajectory via haptic walls at each joint. These arm movements focus training of interjoint coordination with highly intuitive real-time feedback of performance; arm movements advance within the trajectory only if their movement coordination is correct. In initial testing, 37 nondisabled subjects received a single session of learning of a complex pattern. Subjects were randomized to TIFT or visual demonstration or moved along with the robot as it moved though the pattern (time-dependent [TD] training). We examined visual demonstration to separate the effects of action observation on motor learning from the effects of the two haptic guidance methods. During these training trials, TIFT subjects reduced error and interaction forces between the robot and arm, while TD subject performance did not change. All groups showed significant learning of the trajectory during unassisted recall trials, but we observed no difference in learning between groups, possibly because this learning task is dominated by vision. Further testing in stroke populations is warranted.

Effective compression ratio-A new measurement of the quality of thorax compression during CPR

PURPOSE: Computer-based feedback systems for assessing the quality of cardiopulmonary resuscitation (CPR) are widely used these days. Recordings usually involve compression and ventilation dependent variables. Thorax compression depth, sufficient decompression and correct hand position are displayed but interpreted independently of one another. We aimed to generate a parameter, which represents all the combined relevant parameters of compression to provide a rapid assessment of the quality of chest compression-the effective compression ratio (ECR). METHODS: The following parameters were used to determine the ECR: compression depth, correct hand position, correct decompression and the proportion of time used for chest compressions compared to the total time spent on CPR. Based on the ERC guidelines, we calculated that guideline compliant CPR (30:2) has a minimum ECR of 0.79. To calculate the ECR, we expanded the previously described software solution. In order to demonstrate the usefulness of the new ECR-parameter, we first performed a PubMed search for studies that included correct compression and no-flow time, after which we calculated the new parameter, the ECR. RESULTS: The PubMed search revealed 9 trials. Calculated ECR values ranged between 0.03 (for basic life support [BLS] study, two helpers, no feedback) and 0.67 (BLS with feedback from the 6th minute). CONCLUSION: ECR enables rapid, meaningful assessment of CPR and simplifies the comparability of studies as well as the individual performance of trainees. The structure of the software solution allows it to be easily adapted to any manikin, CPR feedback devices and different resuscitation guidelines (e.g. ILCOR, ERC).

Histamine increases sphingosine kinase-1 expression and activity in the human arterial endothelial cell line EA.hy 926 by a PKC-alpha-dependent mechanism

Sphingosine 1-phosphate (S1P) is a potent mitogenic signal generated from sphingosine by the action of sphingosine kinases (SKs). In this study, we show that in the human arterial endothelial cell line EA.hy 926 histamine induces a time-dependent upregulation of the SK-1 mRNA and protein expression which is followed by increased SK-1 activity. A similar upregulation of SK-1 is also observed with the direct protein kinase C activator 12-O-tetradecanoylphorbol-13-acetate (TPA). In contrast, SK-2 activity is not affected by neither histamine nor TPA. The increased SK-1 protein expression is due to stimulated de novo synthesis since cycloheximide inhibited the delayed SK-1 protein upregulation. Moreover, the increased SK-1 mRNA expression results from an increased promoter activation by histamine and TPA. In mechanistic terms, the transcriptional upregulation of SK-1 is dependent on PKC and the extracellular signal-regulated protein kinase (ERK) cascade since staurosporine and the MEK inhibitor U0126 abolish the TPA-induced SK-1 induction. Furthermore, the histamine effect is abolished by the H1-receptor antagonist diphenhydramine, but not by the H2-receptor antagonist cimetidine. Parallel to the induction of SK-1, histamine and TPA stimulate an increased migration of endothelial cells, which is prevented by depletion of the SK-1 by small interfering RNA (siRNA). To appoint this specific cell response to a specific PKC isoenzyme, siRNA of PKC-alpha, -delta, and -epsilon were used to selectively downregulate the respective isoforms. Interestingly, only depletion of PKC-alpha leads to a complete loss of TPA- and histamine-triggered SK-1 induction and cell migration. In summary, these data show that PKC-alpha activation in endothelial cells by histamine-activated H1-receptors, or by direct PKC activators leads to a sustained upregulation of the SK-1 protein expression and activity which, in turn, is critically involved in the mechanism of endothelial cell migration.

Marginal Structural Models for Partial Exposure Regimes

Intensive care unit (ICU) patients are ell known to be highly susceptible for nosocomial (i.e. hospital-acquired) infections due to their poor health and many invasive therapeutic treatments. The effects of acquiring such infections in ICU on mortality are however ill understood. Our goal is to quantify these effects using data from the National Surveillance Study of Nosocomial Infections in Intensive Care Units (Belgium). This is a challenging problem because of the presence of time-dependent confounders (such as exposure to mechanical ventilation)which lie on the causal path from infection to mortality. Standard statistical analyses may be severely misleading in such settings and have shown contradicting results. While inverse probability weighting for marginal structural models can be used to accommodate time-dependent confounders, inference for the effect of ?ICU acquired infections on mortality under such models is further complicated (a) by the fact that marginal structural models infer the effect of acquiring infection on a given, fixed day ?in ICU?, which is not well defined when ICU discharge comes prior to that day; (b) by informative censoring of the survival time due to hospital discharge; and (c) by the instability of the inverse weighting estimation procedure. We accommodate these problems by developing inference under a new class of marginal structural models which describe the hazard of death for patients if, possibly contrary to fact, they stayed in the ICU for at least a given number of days s and acquired infection or not on that day. Using these models we estimate that, if patients stayed in the ICU for at least s days, the effect of acquiring infection on day s would be to multiply the subsequent hazard of death by 2.74 (95 per cent conservative CI 1.48; 5.09).

MRI follow-up of TNF-dependent differential progression of atherosclerotic wall-thickening in mouse aortic arch from early to advanced stages

OBJECTIVES: An optimized, longitudinal in vivo magnetic resonance vessel wall-imaging protocol was evaluated regarding its capability of detecting differences in the time-dependent atherosclerotic lesion progression in the aortic arch between ApoE(-/-) and double-deficient ApoE(-/-)/TNF(-/-) mice at comparatively early plaque development stages. MATERIALS AND METHODS: Seven ApoE(-/-) and seven ApoE(-/-)/TNF(-/-) female mice underwent MRI at 11.75 teslas at four stages up to 26 weeks of age. A double-gated spin-echo MRI sequence was used with careful perpendicular slice positioning to visualize the vessel wall of the ascending aortic arch. RESULTS: Wall-thickness progression measured with MRI was significant at 11 weeks of age in ApoE(-/-) mice, but only at 26 weeks in ApoE(-/-)/TNF(-/-) mice. A significant correlation was found between MRI wall-thickness and lesion area determined on histology. CONCLUSION: MRI was shown to be sensitive enough to reveal subtle genetically-induced differences in lesion progression at ages earlier than 25 weeks.

Towards greater accuracy in individual-tree mortality regression

Background mortality is an essential component of any forest growth and yield model. Forecasts of mortality contribute largely to the variability and accuracy of model predictions at the tree, stand and forest level. In the present study, I implement and evaluate state-of-the-art techniques to increase the accuracy of individual tree mortality models, similar to those used in many of the current variants of the Forest Vegetation Simulator, using data from North Idaho and Montana. The first technique addresses methods to correct for bias induced by measurement error typically present in competition variables. The second implements survival regression and evaluates its performance against the traditional logistic regression approach. I selected the regression calibration (RC) algorithm as a good candidate for addressing the measurement error problem. Two logistic regression models for each species were fitted, one ignoring the measurement error, which is the “naïve” approach, and the other applying RC. The models fitted with RC outperformed the naïve models in terms of discrimination when the competition variable was found to be statistically significant. The effect of RC was more obvious where measurement error variance was large and for more shade-intolerant species. The process of model fitting and variable selection revealed that past emphasis on DBH as a predictor variable for mortality, while producing models with strong metrics of fit, may make models less generalizable. The evaluation of the error variance estimator developed by Stage and Wykoff (1998), and core to the implementation of RC, in different spatial patterns and diameter distributions, revealed that the Stage and Wykoff estimate notably overestimated the true variance in all simulated stands, but those that are clustered. Results show a systematic bias even when all the assumptions made by the authors are guaranteed. I argue that this is the result of the Poisson-based estimate ignoring the overlapping area of potential plots around a tree. Effects, especially in the application phase, of the variance estimate justify suggested future efforts of improving the accuracy of the variance estimate. The second technique implemented and evaluated is a survival regression model that accounts for the time dependent nature of variables, such as diameter and competition variables, and the interval-censored nature of data collected from remeasured plots. The performance of the model is compared with the traditional logistic regression model as a tool to predict individual tree mortality. Validation of both approaches shows that the survival regression approach discriminates better between dead and alive trees for all species. In conclusion, I showed that the proposed techniques do increase the accuracy of individual tree mortality models, and are a promising first step towards the next generation of background mortality models. I have also identified the next steps to undertake in order to advance mortality models further.

Accounting for baseline differences and measurement error in the analysis of change over time

If change over time is compared in several groups, it is important to take into account baseline values so that the comparison is carried out under the same preconditions. As the observed baseline measurements are distorted by measurement error, it may not be sufficient to include them as covariate. By fitting a longitudinal mixed-effects model to all data including the baseline observations and subsequently calculating the expected change conditional on the underlying baseline value, a solution to this problem has been provided recently so that groups with the same baseline characteristics can be compared. In this article, we present an extended approach where a broader set of models can be used. Specifically, it is possible to include any desired set of interactions between the time variable and the other covariates, and also, time-dependent covariates can be included. Additionally, we extend the method to adjust for baseline measurement error of other time-varying covariates. We apply the methodology to data from the Swiss HIV Cohort Study to address the question if a joint infection with HIV-1 and hepatitis C virus leads to a slower increase of CD4 lymphocyte counts over time after the start of antiretroviral therapy.

AMR-Me inhibits PI3K/Akt signaling in hormone-dependent MCF-7 breast cancer cells and inactivates NF-κB in hormone-independent MDA-MB-231 cells

AMR-Me, a C-28 methylester derivative of triterpenoid compound Amooranin isolated from Amoora rohituka stem bark and the plant has been reported to possess multitude of medicinal properties. Our previous studies have shown that AMR-Me can induce apoptosis through mitochondrial apoptotic and MAPK signaling pathways by regulating the expression of apoptosis related genes in human breast cancer MCF-7 cells. However, the molecular mechanism of AMR-Me induced apoptotic cell death remains unclear. Our results showed that AMR-Me dose-dependently inhibited the proliferation of MCF-7 and MDA-MB-231 cells under serum-free conditions supplemented with 1 nM estrogen (E2) with an IC50 value of 0.15 µM, 0.45 µM, respectively. AMR-Me had minimal effects on human normal breast epithelial MCF-10A + ras and MCF-10A cells with IC50 value of 6 and 6.5 µM, respectively. AMR-Me downregulated PI3K p85, Akt1, and p-Akt in an ERα-independent manner in MCF-7 cells and no change in expression levels of PI3K p85 and Akt were observed in MDA-MB-231 cells treated under similar conditions. The PI3K inhibitor LY294002 suppressed Akt activation similar to AMR-Me and potentiated AMR-Me induced apoptosis in MCF-7 cells. EMSA revealed that AMR-Me inhibited nuclear factor-kappaB (NF-κB) DNA binding activity in MDA-MB-231 cells in a time-dependent manner and abrogated EGF induced NF-κB activation. From these studies we conclude that AMR-Me decreased ERα expression and effectively inhibited Akt phosphorylation in MCF-7 cells and inactivate constitutive nuclear NF-κB and its regulated proteins in MDA-MB-231 cells. Due to this multifactorial effect in hormone-dependent and independent breast cancer cells AMR-Me deserves attention for use in breast cancer prevention and therapy

Effects of anxiety on decision making and visual search behaviour in complex sport situations

Introduction Current empirical findings indicate that the efficiency of decision making (both for experts and near-experts) in simple situations is reduced under increased stress (Wilson, 2008). Explaining the phenomenon, the Attentional Control Theory (ACT, Eysenck et al., 2007) postulates an impairment of attentional processes resulting in a less efficient processing of visual information. From a practitioner’s perspective, it would be highly relevant to know whether this phenomenon can also be found in complex sport situations like in the game of football. Consequently, in the present study, decision making of football players was examined under regular vs. increased anxiety conditions. Methods 22 participants (11 experts and 11 near-experts) viewed 24 complex football situations (counterbalanced) in two anxiety conditions from the perspective of the last defender. They had to decide as fast and accurate as possible on the next action of the player in possession (options: shot on goal, dribble or pass to a designated team member) for equal numbers of trials in a near and far distance condition (based on the position of the player in possession). Anxiety was manipulated via a competitive environment, false feedback as well as ego threats. Decision time and accuracy, gaze behaviour (e.g., fixation duration on different locations) as well as state anxiety and mental effort were used as dependent variables and analysed with 2 (expertise) x 2 (distance) x 2 (anxiety) ANOVAs with repeated measures on the last two factors. Besides expertise differences, it was hypothesised that, based on ACT, increased anxiety reduces performance efficiency and impairs gaze behaviour. Results and Discussion Anxiety was manipulated successfully, indicated by higher ratings of state anxiety, F(1, 20) = 13.13, p < .01, ηp2 = .40. Besides expertise differences in decision making – experts responded faster, F(1, 20) = 11.32, p < .01, ηp2 = .36, and more accurate, F(1,20) = 23.93, p < .01, ηp2 = .55, than near-experts – decision time, F(1, 20) = 9.29, p < .01, ηp2 = .32, and mental effort, F(1, 20) = 7.33, p = .01, ηp2 = .27, increased for both groups in the high anxiety condition. This result confirms the ACT assumption that processing efficiency is reduced when being anxious. Replicating earlier findings, a significant expertise by distance interaction could be observed, F(1, 18) = 18.53, p < .01, ηp2 = .51), with experts fixating longer on the player in possession or the ball in the near distance and longer on other opponents, teammates and free space in the far distance condition. This shows that experts are able to adjust their gaze behaviour to affordances of displayed playing patterns. Additionally, a three way interaction was found, F(1, 18) = 7.37 p = .01, ηp2 = .29, revealing that experts utilised a reduced number of fixations in the far distance condition when being anxious indicating a reduced ability to pick up visual information. Since especially the visual search behaviour of experts was impaired, the ACT prediction that particularly top-down processes are affected by anxiety could be confirmed. Taken together, the results show that sports performance is negatively influenced by anxiety since longer response times, higher mental effort and inefficient visual search behaviour were observed. From a practitioner’s perspective, this finding might suggest preferring (implicit) perceptual cognitive training; however, this recommendation needs to be empirically supported in intervention studies. References: Eysenck, M. W., Derakshan, N., Santos, R., & Calvo, M. G. (2007). Anxiety and cognitive performance: Attentional control theory. Emotion, 7, 336-353. Wilson, M. (2008). From processing efficiency to attentional control: A mechanistic account of the anxiety-performance relationship. Int. Review of Sport and Exercise Psychology, 1, 184-201.